Semantics in Business Systems: The Savvy Manager’s Guide 1st edition by Dave McComb 2 – Ebook PDF Instant Download/Delivery. 1558609172, 978-1558609174
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ISBN 10: 1558609172
ISBN 13: 978-1558609174
Author: Dave McComb
Semantics in Business Systems begins with a description of what semantics are and how they affect business systems. It examines four main aspects of the application of semantics to systems, specifically: How do we infer meaning from unstructured information, how do application systems make meaning as they operate, how do practitioners uncover meaning in business settings, and how do we understand and communicate what we have deduced? This book illustrates how this applies to the future of application system development, especially how it informs and affects Web services and business rule- based approaches, and how semantics will play out with XML and the semantic Web. The book also contains a quick reference guide to related terms and technologies. It is part of Morgan Kaufmann’s series of Savvy Manager’s Guides.
Semantics in Business Systems: The Savvy Manager’s Guide 1st Table of contents:
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Introduction to Semantics in Business Systems
- Overview of Semantics and Its Role in Business Systems
- The Importance of Understanding Meaning in Data and Information
- Semantics vs. Syntax: Key Differences and Implications
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Chapter 1: The Basics of Semantics
- Defining Semantics in the Context of Business Systems
- Types of Semantics: Lexical, Compositional, Pragmatic
- How Semantics Affects Data Interpretation and Decision-Making
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Chapter 2: Semantics and Business Processes
- Linking Semantics to Business Processes and Operations
- The Role of Meaning in Business Process Modeling and Automation
- Real-World Examples of Semantics in Business Processes
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Chapter 3: Data and Information Management
- Data vs. Information: The Importance of Context and Meaning
- The Challenges of Managing Semantic Data in Business Systems
- Techniques for Improving Data Quality and Relevance
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Chapter 4: Semantic Models and Frameworks
- Introduction to Semantic Modeling
- Ontologies, Taxonomies, and Controlled Vocabularies in Business Systems
- Using Semantic Models for Decision Support and Knowledge Management
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Chapter 5: Semantics in Enterprise Architecture
- Role of Semantics in System Design and Integration
- Ensuring Consistent Meaning Across Enterprise Systems
- Aligning IT Infrastructure with Business Goals Using Semantics
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Chapter 6: Managing Knowledge with Semantics
- Knowledge Management and the Role of Semantics
- The Use of Semantic Technologies in Knowledge Sharing and Collaboration
- Building Knowledge Repositories with Semantic Structuring
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Chapter 7: Business Intelligence and Analytics
- The Role of Semantics in Data Analytics and Reporting
- Enhancing Business Intelligence with Meaningful Data
- Semantic Technologies for Advanced Data Analysis
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Chapter 8: Communication and Semantics
- How Semantics Influences Business Communication and Decision Making
- Aligning Stakeholder Understanding Through Shared Semantics
- Using Semantics for Effective Collaboration in Teams
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Chapter 9: Implementing Semantics in Business Systems
- Challenges and Strategies for Implementing Semantics in Existing Systems
- Tools and Technologies for Managing Semantics
- Best Practices for Semantic Integration
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Chapter 10: The Future of Semantics in Business Systems
- Emerging Trends and Technologies in Semantic Business Systems
- The Impact of AI, Machine Learning, and NLP on Semantics
- Preparing for the Next Evolution of Semantic Business Solutions
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Conclusion
- Recap of the Importance of Semantics for Managers
- Final Thoughts on Leveraging Semantics for Business Success
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Appendices
- Glossary of Key Terms and Concepts
- Further Reading and Resources
- Index
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